Physics-based continuum, electrochemical battery models were initially developed in the 1960's [1]} and have since been adapted to a range of battery chemistries, including lead-acid [2]}, nickel/metal hydride [3]}, lithium-air [4]}, and lithium-ion [5]}, [6]}, [7]}, [8]}. The latter is commonly referred to as the Doyle-Fuller-Newman (DFN) model and it has dominated battery continuum modelling since the early 1990’s. Reductions of the aforementioned physics-based models started with the single particle model proposed by Atlung et al. [9]} and was later extended by Prada et al. [10]} to include the lithium-ion distribution in the electrolyte. Single Particle Models (SPMs) assume that all the particles within an electrode can be represented by a single spherical particle, and thus significantly reduce the complexity of the model. These physics-based, electrochemical models also provide insight into the behaviour of the multiple internal variables, as depicted in Figure REF , which cannot easily be measured in an in operando set-up. In particular, they describe the potential and current distributions in both the porous electrodes and the electrolyte, the lithium ion concentration within the electrolyte and the distribution of intercalated lithium within the electrode particles. When properly implemented and calibrated, these models can provide fast and accurate predictions of real batteries, which have many possible applications. For example, they can be used as a design tool, in order to facilitate new electrode, cell and pack architectures and to assess their potential performance, thereby minimising the need for expensive prototyping. Model simulations can also be used to determine which of the many types of batteries available on the market best fit a particular use case. Other possible uses include: thermal management, in operando control, battery monitoring and lifetime estimation.
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